Pinecone: Vector Database Solutions for AI Training Course

H2O AutoML is an artificial intelligence platform that automates the process of building, selecting and optimizing large numbers of machine learning models.

This instructor-led, live training (online or onsite) is aimed at data scientists who wish to use H2O AutoML to automate the process of building and selecting the best machine learning algorithm and parameters.

By the end of this training, participants will be able to:

• Automate the machine learning workflow.
• Automatically train and tune many machine learning models within a specified time range.
• Train stacked ensembles to arrive at highly predictive ensemble models.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Auto-sklearn is a Python package built around the scikit-learn machine learning library. It automatically searches for the right learning algorithm for a new machine learning dataset and optimizes its parameters.

This instructor-led, live training (online or onsite) is aimed at machine learning practitioners who wish to use Auto-sklearn to automate the process of selecting and optimizing a machine learning model.

By the end of this training, participants will be able to:

• Automate the process of training highly efficient machine learning models.
• Build highly accurate machine learning models while bypassing the more tedious tasks of selecting, training and testing different models.
• Use the power of machine learning to solve real-world business problems.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Auto-Keras (Also known as Autokeras or Auto Keras) is an open source Python library for automated machine learning (AutoML).

This instructor-led, live training (online or onsite) is aimed at data scientists as well as less technical persons who wish to use Auto-Keras to automate the process of selecting and optimizing a machine learning model.

By the end of this training, participants will be able to:

• Automate the process of training highly efficient machine learning models.
• Automatically search for the best parameters for deep learning models.
• Build highly accurate machine learning models.
• Use the power of machine learning to solve real-world business problems.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.
• To learn more about Auto-Keras, please visit: https://autokeras.com/

Stable Diffusion adalah model pembelajaran mendalam yang kuat yang dapat menghasilkan gambar terperinci berdasarkan deskripsi teks.

Pelatihan langsung yang dipandu instruktur (online atau di tempat) ini ditujukan untuk ilmuwan data, insinyur pembelajaran mesin, dan peneliti visi komputer yang ingin memanfaatkan Stable Diffusion untuk menghasilkan gambar berkualitas tinggi untuk berbagai kasus penggunaan.

Pada akhir pelatihan ini, peserta akan dapat:

Pahami prinsip Stable Diffusion dan cara kerjanya untuk pembuatan gambar. Buat dan latih model Stable Diffusion untuk tugas pembuatan gambar. Terapkan Stable Diffusion ke berbagai skenario pembuatan gambar, seperti inpainting, outpainting, dan terjemahan gambar ke gambar. Optimalkan performa dan stabilitas model Stable Diffusion.

Format Kursus

Kuliah dan diskusi interaktif. Banyak latihan dan latihan. Implementasi langsung di lingkungan lab langsung.

Opsi Penyesuaian Kursus

Untuk meminta pelatihan khusus untuk kursus ini, silakan hubungi kami untuk mengaturnya.

Stable Diffusion adalah model pembelajaran mendalam yang kuat yang dapat menghasilkan gambar terperinci berdasarkan deskripsi teks.

Pelatihan langsung yang dipandu instruktur (online atau di tempat) ini ditujukan untuk ilmuwan data tingkat menengah hingga mahir, insinyur pembelajaran mesin, peneliti pembelajaran mendalam, dan pakar visi komputer yang ingin memperluas pengetahuan dan keterampilan mereka dalam pembelajaran mendalam untuk teks-ke -generasi gambar.

Pada akhir pelatihan ini, peserta akan dapat:

Memahami arsitektur dan teknik deep learning tingkat lanjut untuk pembuatan teks-ke-gambar. Terapkan model dan pengoptimalan yang kompleks untuk sintesis gambar berkualitas tinggi. Optimalkan performa dan skalabilitas untuk kumpulan data besar dan model kompleks. Sesuaikan hyperparameter untuk performa dan generalisasi model yang lebih baik. Integrasikan Stable Diffusion dengan kerangka kerja dan alat pembelajaran mendalam lainnya.

Format Kursus

Kuliah dan diskusi interaktif. Banyak latihan dan latihan. Implementasi langsung di lingkungan lab langsung.

Opsi Penyesuaian Kursus

Untuk meminta pelatihan khusus untuk kursus ini, silakan hubungi kami untuk mengaturnya.

AlphaFold adalah sistem Artificial Intelligence (AI) yang melakukan prediksi struktur protein. Ini dikembangkan oleh Alphabet’s/Google’s DeepMind sebagai sistem pembelajaran mendalam yang dapat memprediksi dengan tepat model 3D struktur protein.

Pelatihan langsung yang dipimpin oleh instruktur (online atau on-site) ini ditujukan untuk ahli biologi yang ingin memahami bagaimana AlphaFold bekerja dan menggunakan AlphaFold model sebagai panduan dalam studi eksperimental mereka.

Pada akhir latihan ini, peserta akan dapat:

Memahami prinsip dasar dari AlphaFold. Ketahui bagaimana 2 (dua) bekerja. Pelajari cara menginterpretasikan AlphaFold prediksi dan hasil.

Format Kursus

Konferensi dan diskusi interaktif. Banyak latihan dan praktek. Pelaksanaan tangan di lingkungan live-lab.

Opsi Customization Kursus

Untuk meminta pelatihan tersuai untuk kursus ini, silakan hubungi kami untuk mengatur.

TensorFlow Lite is an open source deep learning framework for executing models on mobile and embedded devices with limited compute and memory resources.

This instructor-led, live training (online or onsite) is aimed at developers who wish to use TensorFlow Lite to deploy deep learning models on embedded devices.

By the end of this training, participants will be able to:

• Install and configure Tensorflow Lite on an embedded device.
• Understand the concepts and components underlying TensorFlow Lite.
• Convert existing machine learning models to TensorFlow Lite format for execution on embedded devices.
• Work within the limitations of small devices and TensorFlow Lite, while learning how to expand their default capabilities.
• Deploy deep learning models on embedded devices running Linux to solve physical world problems such as recognizing images and voice, predicting patterns, and initiating movements and responses from robots and other embedded systems in the field.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

TensorFlow Lite is an open source deep learning framework for mobile devices and embedded systems.

This instructor-led, live training (online or onsite) is aimed at developers who wish to use TensorFlow Lite to develop mobile applications with deep learning capabilities.

By the end of this training, participants will be able to:

• Install and configure TensorFlow Lite.
• Understand the principles behind TensorFlow, machine learning and deep learning.
• Load TensorFlow Models onto an Android device.
• Enable deep learning and machine learning functionality such as computer vision and natural language recognition in a mobile application.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.
• To learn more about TensorFlow, please visit: https://www.tensorflow.org/lite/

TensorFlow Lite for Microcontrollers is a port of TensorFlow Lite designed to run machine learning models on microcontrollers and other devices with limited memory.

This instructor-led, live training (online or onsite) is aimed at engineers who wish to write, load and run machine learning models on very small embedded devices.

By the end of this training, participants will be able to:

• Install TensorFlow Lite.
• Load machine learning models onto an embedded device to enable it to detect speech, classify images, etc.
• Add AI to hardware devices without relying on network connectivity.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

TensorFlow Lite is an open source deep learning framework for mobile devices and embedded systems.

This instructor-led, live training (online or onsite) is aimed at developers who wish to use TensorFlow Lite to develop iOS mobile applications with deep learning capabilities.

By the end of this training, participants will be able to:

• Install and configure TensorFlow Lite.
• Understand the principles behind TensorFlow and machine learning on mobile devices.
• Load TensorFlow Models onto an iOS device.
• Run an iOS application capable of detecting and classifying an object captured through the device's camera.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Chainer is an open source framework based on Python, built for accelerating research and implementing neural network models. It provides flexible, efficient, and simplified approaches to developing deep learning algorithms.

This instructor-led, live training (online or onsite) is aimed at researchers and developers who wish to use Chainer to build and train neural networks in Python while making the code easy to debug.

By the end of this training, participants will be able to:

• Set up the necessary development environment to start developing neural network models.
• Define and implement neural network models using a comprehensible source code.
• Execute examples and modify existing algorithms to optimize deep learning training models while leveraging GPUs for high performance.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Horovod is an open source software framework, designed for processing fast and efficient distributed deep learning models using TensorFlow, Keras, PyTorch, and Apache MXNet. It can scale up a single-GPU training script to run on multiple GPUs or hosts with minimal code changes.

This instructor-led, live training (online or onsite) is aimed at developers or data scientists who wish to use Horovod to run distributed deep learning trainings and scale it up to run across multiple GPUs in parallel.

By the end of this training, participants will be able to:

• Set up the necessary development environment to start running deep learning trainings.
• Install and configure Horovod to train models with TensorFlow, Keras, PyTorch, and Apache MXNet.
• Scale deep learning training with Horovod to run on multiple GPUs.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• This course is focused on Horovod, but other software tools and frameworks such as TensorFlow, Keras, PyTorch, and Apache MXNet may be required. Please let us know if you have specific requirements or preferences.
• To request a customized training for this course, please contact us to arrange.

An FPGA (Field Programmable Gate Array) is an integrated circuit that can be used to accelerate deep learning computations. OpenVINO is an open source toolkit for optimizing Deep Learning models on Intel hardware.

This instructor-led, live training (online or onsite) is aimed at data scientists who wish to accelerate real-time machine learning applications and deploy them at scale.

By the end of this training, participants will be able to:

• Install the OpenVINO toolkit.
• Accelerate a computer vision application using an FPGA.
• Execute different CNN layers on the FPGA.
• Scale the application across multiple nodes in a Kubernetes cluster.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

MXNet is a flexible, open-source Deep Learning library that is popular for research prototyping and production. Together with the high-level Gluon API interface, Apache MXNet is a powerful alternative to TensorFlow and PyTorch.

This instructor-led, live training (online or onsite) is aimed at data scientists who wish to use Apache MXNet to build and deploy a deep learning model for image recognition.

By the end of this training, participants will be able to:

• Install and configure Apache MXNet and its components.
• Understand MXNet's architecture and data structures.
• Use Apache MXNet's low-level and high-level APIs to efficiently build neural networks.
• Build a convolutional neural network for image classification.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Keras is a high-level neural networks API for fast development and experimentation. It runs on top of TensorFlow, CNTK, or Theano.

This instructor-led, live training (online or onsite) is aimed at technical persons who wish to apply deep learning model to image recognition applications.

By the end of this training, participants will be able to:

• Install and configure Keras.
• Quickly prototype deep learning models.
• Implement a convolutional network.
• Implement a recurrent network.
• Execute a deep learning model on both a CPU and GPU.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.
• To learn more about Keras, please visit: https://keras.io/